Schematic methods for probabilistic enzyme kinetics.

The theory of steady-state enzyme processes which avoids using the mass action law of chemical kinetics and consistently describes catalytic mechanisms by probabilistic concepts has recently been proposed (Mazur, 1991, J. theor. Biol. 148, 229-242). To facilitate the analysis of complex reaction graphs by this theory the possibility of constructing schematic rules similar to those used in classical kinetics is studied. It is found that due to the similarity of algebraic procedures the popular method of King & Altman can be applied in probabilistic kinetics in addition to the earlier proposed rule based on enumeration of cycles of the reaction graph. This similarity also allows one to adapt many other shortcut methods of classical kinetics for probabilistic reaction graphs. The paper considers separately the possibility of transforming reaction mechanisms so that the initial graph is replaced by a simpler but equivalent one. It is shown that there are few cases when a group of states can be replaced by one united state, with earlier known rules such as the rule of Cha for equilibrium stages being particular cases of a more general procedure. In addition a novel method is proposed which performs step-by-step reduction of any reaction graph. All the new methods can be adapted for traditional kinetics as well. The results obtained demonstrate that many schematic rules of classical kinetics are of probabilistic origin.     

Fuzzy chorotypes as a conceptual tool to improve insight into biogeographic patterns

Chorotypes--statistically significant groups of coincident distribution areas--constitute biogeographic units that are fuzzy by nature. This quality has been referred to in the literature but has not been analyzed in depth or methodologically developed. The present work redefines chorotypes as fuzzy sets from a pragmatic perspective and basically focuses on the methodological and interpretative implications of this approach. The amphibian fauna in the Iberian Peninsula was used as an example to explore the fuzzy nature of chorotypes. The method on which this article is based is a widely used technique to define chorotypes. This method involves the fuzziness that is inherent to the identification between degree of similarity and degree of membership and includes a probabilistic analysis of the classification for the objective delimitation of chorotypes. The main innovation of this paper is a procedure to analyze chorotypes as fuzzy biogeographic units. A set of fuzzy parameters to deal with the biogeographic interpretation of fuzzy chorotypes is also described. A computer program has been developed and is freely available. History may be related to the degree of fuzziness of chorotypes. In our example, with amphibian distributions in Iberia, less fuzzy chorotypes could have a historical explanation, and the internal fuzziness of chorotypes increases with their distance to hypothetical Pleistocene refugia.     

Reciprocal illumination in the gene content tree of life

Phylogenies based on gene content rely on statements of primary homology to characterize gene presence or absence. These statements (hypotheses) are usually determined by techniques based on threshold similarity or distance measurements between genes. This fundamental but problematic step can be examined by evaluating each homology hypothesis by the extent to which it is corroborated by the rest of the data. Here we test the effects of varying the stringency for making primary homology statements using a range of similarity (e-value) cutoffs in 166 fully sequenced and annotated genomes spanning the tree of life. By evaluating each resulting data set with tree-based measurements of character consistency and information content, we find a set of homology statements that optimizes overall corroboration. The resulting data set produces well-resolved and well-supported trees of life and greatly ameliorates previously noted inconsistencies such as the misclassification of small genomes. The method presented here, which can be used to test any technique for recognizing primary homology, provides an objective framework for evaluating phylogenetic hypotheses and data sets for the tree of life. It also can serve as a technique for identifying well-corroborated sets of homologous genes for functional genomic applications.     

Intervals for the assessment of measurement agreement: Similarities,differences, and consequences of incorrect interpretations

Several intervals have been proposed to quantify the agreement of two methods intended to measure the same quantity in the situation where only one measurement per method and subject is available. The limits of agreement are probably the most well‐known among these intervals, which are all based on the differences between the two measurement methods. The different meanings of the intervals are not always properly recognized in applications. However, at least for small‐to‐moderate sample sizes, the differences will be substantial. This is illustrated both using the width of the intervals and on probabilistic scales related to the definitions of the intervals. In particular, for small‐to‐moderate sample sizes, it is shown that limits of agreement and prediction intervals should not be used to make statements about the distribution of the differences between the two measurement methods or about a plausible range for all future differences. Care should therefore be taken to ensure the correct choice of the interval for the intended interpretation.     

Reduced scale model qualification of 5-L and 250-ml bioreactors using multivariant visualization and Bayesian inferential methods

A novel method for the qualification of reduced scale models (RSMs) was illustrated using data from both a 250-ml advanced microscale bioreactor (ambr) and a 5-L bioreactor RSM for a 2,000-L manufacturing scale process using a CHO cell line to produce a recombinant monoclonal antibody. The example study showed how the method was used to identify process performance attributes and product quality attributes that capture important aspects of the RSM qualification process. The method uses two novel statistical approaches: multivariate dimension reduction and data visualization techniques, via partial least squares discriminant analysis (PLS-DA), and Bayesian multivariate linear modeling for inferential analysis. Bayesian multivariate linear modeling allows for individual probability distributions of the differences of the mean of each attribute for each scale, as well as joint probability statements on the differences of the means for multiple attributes. Depending on the results of this inferential procedure, PLS-DA is used to identify the process performance outputs at the different scales which have the greatest negative impact on the multivariate Bayesian joint probabilities. Experience with that particular process can then be leveraged to adjust operating conditions to minimize these differences, and then equivalence can be reassessed using the multivariate linear model.     

Priming of aggressive motivation in Betta splendens

Swimming speed in a runway for a view of a conspecific was shown to be positively correlated with vigour of aggressive display prior to the experiment. A priming procedure (pre-exposure to a conspecific), and decreasing the time between trials, were then shown to increase swimming speed. Priming also increased the choice for a conspecific over food, but only in the presence of particular external stimuli. These results are interpreted to mean that the level of aggressive motivation is determined by a complex interaction of internal and external factors, and that there is a high degree of similarity between aggression and other motivations such as hunger and thirst.     

APPLICATIONS OF SENSORY SCIENCE WITHIN THE TOBACCO INDUSTRY

Sensory testing of cigarette smoke presents some unique problems to the sensory specialist. This is due to a variety of reasons including the high degree of similarity between blended cigarettes and a high degree of variability between individual cigarettes. In the cigarette industry, a large effort has been placed on adapting and developing new methods of collecting and analyzing sensory-data on both flavorants and cigarette smoke. These methods include odor profiling and multidimensional scaling based on attributes and acceptability scales. In addition, extensive research has been conducted to determine the number of relevent dimensions to smoking and the types of changes that could affect consumer acceptance or purchase behavior.     

Analysis of several biomechanical models for the simulation of lamb liver behaviour using similarity coefficients from medical image

In this study, six biomechanical models for simulating lamb liver behaviour are presented. They are validated using similarity coefficients from Medical Image on reconstructed volumes from computerised tomography images. In particular, the Jaccard and Hausdorff coefficients are used. Loads of 20 and 40 g are applied to the livers and their deformation is simulated by means of the finite element method. The models used are a linear elastic model, a neo-Hookean model, a Mooney–Rivlin model, an Ogden model, a linear viscoelastic model and a viscohyperelastic model. The model that provided a behaviour that is closest to reality was the viscohyperelastic model, where the hyperelastic part was modelled with an Ogden model.     

P-value based visualization of codon usage data

Two important and not yet solved problems in bacterial genome research are the identification of horizontally transferred genes and the prediction of gene expression levels. Both problems can be addressed by multivariate analysis of codon usage data. In particular dimensionality reduction methods for visualization of multivariate data have shown to be effective tools for codon usage analysis. We here propose a multidimensional scaling approach using a novel similarity measure for codon usage tables. Our probabilistic similarity measure is based on P-values derived from the well-known chi-square test for comparison of two distributions. Experimental results on four microbial genomes indicate that the new method is well-suited for the analysis of horizontal gene transfer and translational selection. As compared with the widely-used correspondence analysis, our method did not suffer from outlier sensitivity and showed a better clustering of putative alien genes in most cases.     

Gene Clustering via Integrated Markov Models Combining Individual and Pairwise Features

Clustering of genes into groups sharing common characteristics is a useful exploratory technique for a number of subsequent computational analysis. A wide range of clustering algorithms have been proposed in particular to analyze gene expression data, but most of them consider genes as independent entities or include relevant information on gene interactions in a suboptimal way. We propose a probabilistic model that has the advantage to account for individual data (e.g., expression) and pairwise data (e.g., interaction information coming from biological networks) simultaneously. Our model is based on hidden Markov random field models in which parametric probability distributions account for the distribution of individual data. Data on pairs, possibly reflecting distance or similarity measures between genes, are then included through a graph, where the nodes represent the genes, and the edges are weighted according to the available interaction information. As a probabilistic model, this model has many interesting theoretical features. In addition, preliminary experiments on simulated and real data show promising results and points out the gain in using such an approach. Availability: The software used in this work is written in C++ and is available with other supplementary material at http://mistis.inrialpes.fr/people/forbes/transparentia/supplementary.html.     

A Supervised Approach to Quantifying Sentence Similarity: With Application to Evidence Based Medicine

Following the Evidence Based Medicine (EBM) practice, practitioners make use of the existing evidence to make therapeutic decisions. This evidence, in the form of scientific statements, is usually found in scholarly publications such as randomised control trials and systematic reviews. However, finding such information in the overwhelming amount of published material is particularly challenging. Approaches have been proposed to automatically extract scientific artefacts in EBM using standardised schemas. Our work takes this stream a step forward and looks into consolidating extracted artefacts—i.e., quantifying their degree of similarity based on the assumption that they carry the same rhetorical role. By semantically connecting key statements in the literature of EBM, practitioners are not only able to find available evidence more easily, but also can track the effects of different treatments/outcomes in a number of related studies. We devise a regression model based on a varied set of features and evaluate it both on a general English corpus (the SICK corpus), as well as on an EBM corpus (the NICTA-PIBOSO corpus). Experimental results show that our approach performs on par with the state of the art on the general English and achieves encouraging results on the biomedical text when compared against human judgement.     

Behavioral responses to the 2015 MERS epidemic in Korea

Understanding behavioral responses to epidemics is important in evaluating the broad health consequences of emerging infectious diseases. Building on the economic epidemiology literature, this study investigates individual behavioral responses to the 2015 Middle East Respiratory Syndrome Coronavirus (MERS-CoV) epidemic in Korea using a panel of individuals in a nationally representative survey. Results show that exposure to the epidemic led to lasting impacts on smoking and drinking behaviors, indicating that emerging infectious disease outbreaks are motivations for behavioral changes and opportunities for public policy interventions. In particular, individuals in the hardest-hit regions or socially connected persons were more likely to change their risky behaviors, suggesting that intensity of exposure and social interactions are potential mechanisms.     

Profile-profile methods provide improved fold-recognition: a study of different profile-profile alignment methods

To improve the detection of related proteins, it is often useful to include evolutionary information for both the query and target proteins. One method to include this information is by the use of profile-profile alignments, where a profile from the query protein is compared with the profiles from the target proteins. Profile-profile alignments can be implemented in several fundamentally different ways. The similarity between two positions can be calculated using a dot-product, a probabilistic model, or an information theoretical measure. Here, we present a large-scale comparison of different profile-profile alignment methods. We show that the profile-profile methods perform at least 30% better than standard sequence-profile methods both in their ability to recognize superfamily-related proteins and in the quality of the obtained alignments. Although the performance of all methods is quite similar, profile-profile methods that use a probabilistic scoring function have an advantage as they can create good alignments and show a good fold recognition capacity using the same gap-penalties, while the other methods need to use different parameters to obtain comparable performances.     

An International Survey of Aquaponics Practitioners

Aquaponics, a combination of fish farming and soilless plant farming, is growing in popularity and gaining attention as an important and potentially more sustainable method of food production. The aim of this study was to document and analyze the production methods, experiences, motivations, and demographics of aquaponics practitioners in the United States (US) and internationally. The survey was distributed online using a chain sampling method that relied on referrals from initial respondents, with 809 respondents meeting the inclusion criteria. The majority of respondents were from the US (80%), male (78%), and had at least a high school degree (91%). The mean age of respondents was 47±13 years old. Most respondents (52%) had three years or less of aquaponics experience. Respondents typically raised tilapia or ornamental fish and a variety of leafy green vegetables, herbs, and fruiting crops. Respondents were most often motivated to become involved in aquaponics to grow their own food, for environmental sustainability reasons, and for personal health reasons. Many respondents employed more than one method to raise crops, and used alternative or environmentally sustainable sources of energy, water, and fish feed. In general, our findings suggest that aquaponics is a dynamic and rapidly growing field with participants who are actively experimenting with and adopting new technologies. Additional research and outreach is needed to evaluate and communicate best practices within the field. This survey is the first large-scale effort to track aquaponics in the US and provides information that can better inform policy, research, and education efforts regarding aquaponics as it matures and possibly evolves into a mainstream form of agriculture.     

ON SPECIES and OTHER TAXA

Abstract— It is argued that taxa, whether Linnaean or phylogenetic, belong to Popper's worlds 2 and 3, the worlds of knowledge, but that they represent entities residing in world 1, the world of objects, namely, classes of living beings. The Linnaean taxa are concepts, and thus untestable, whereas phylogenetic taxa are statements, the monophyletic taxa being true, and the paraphyletic and polyphyletic ones false statements. The taxa are neither strictly nor numerically universal statements, but probabilistic ones which cannot be falsified by single observations. It is suggested that the classical "species problem" is due to the fact that "species" has been used in three different senses. First, traditionally it has been assumed that the specific "essence" of an organism is that by which it is what it is. When we know the species, we know the organism. Second, the species are terminal taxa in the phylogenetic hierarchy. This implies that it is only a very small part of the "essence" of the organism which distinguishes the species. The remaining part characterizes the succession of superior taxa in the phylogenetic lineage which ends with the species in question. Third, the species has been regarded to be the "evolutionary unit." This idea may be refuted for two reasons: (1) since concepts and statements cannot evolve, species cannot evolve either, and (2) it is generally in very small isolated populations that evolutionary innovations are first established. In Linnean systematics the superior taxa are allotted categorical rank. The fact that the classification is constrained by this conventional stipulation implies that the superior taxa are often man-made artifacts. In the phylogenetic hierarchy, composed of monophyletic taxa, the ontological states of the taxa is completely independent of their numerical rank; the kingdom is as "real" as the species.     

Evaluation of Diffusion-Tensor Imaging-Based Global Search and Tractography for Tumor Surgery Close to the Language System

Pre-operative planning and intra-operative guidance in neurosurgery require detailed information about the location of functional areas and their anatomo-functional connectivity. In particular, regarding the language system, post-operative deficits such as aphasia can be avoided. By combining functional magnetic resonance imaging and diffusion tensor imaging, the connectivity between functional areas can be reconstructed by tractography techniques that need to cope with limitations such as limited resolution and low anisotropic diffusion close to functional areas. Tumors pose particular challenges because of edema, displacement effects on brain tissue and infiltration of white matter. Under these conditions, standard fiber tracking methods reconstruct pathways of insufficient quality. Therefore, robust global or probabilistic approaches are required. In this study, two commonly used standard fiber tracking algorithms, streamline propagation and tensor deflection, were compared with a previously published global search, Gibbs tracking and a connection-oriented probabilistic tractography approach. All methods were applied to reconstruct neuronal pathways of the language system of patients undergoing brain tumor surgery, and control subjects. Connections between Broca and Wernicke areas via the arcuate fasciculus (AF) and the inferior fronto-occipital fasciculus (IFOF) were validated by a clinical expert to ensure anatomical feasibility, and compared using distance- and diffusion-based similarity metrics to evaluate their agreement on pathway locations. For both patients and controls, a strong agreement between all methods was observed regarding the location of the AF. In case of the IFOF however, standard fiber tracking and Gibbs tracking predominantly identified the inferior longitudinal fasciculus that plays a secondary role in semantic language processing. In contrast, global search resolved connections in almost every case via the IFOF which could be confirmed by probabilistic fiber tracking. The results show that regarding the language system, our global search is superior to clinically applied conventional fiber tracking strategies with results similar to time-consuming global or probabilistic approaches.     

Drug Promiscuity in PDB: Protein Binding Site Similarity Is Key

Drug repositioning applies established drugs to new disease indications with increasing success. A pre-requisite for drug repurposing is drug promiscuity (polypharmacology) – a drug’s ability to bind to several targets. There is a long standing debate on the reasons for drug promiscuity. Based on large compound screens, hydrophobicity and molecular weight have been suggested as key reasons. However, the results are sometimes contradictory and leave space for further analysis. Protein structures offer a structural dimension to explain promiscuity: Can a drug bind multiple targets because the drug is flexible or because the targets are structurally similar or even share similar binding sites? We present a systematic study of drug promiscuity based on structural data of PDB target proteins with a set of 164 promiscuous drugs. We show that there is no correlation between the degree of promiscuity and ligand properties such as hydrophobicity or molecular weight but a weak correlation to conformational flexibility. However, we do find a correlation between promiscuity and structural similarity as well as binding site similarity of protein targets. In particular, 71% of the drugs have at least two targets with similar binding sites. In order to overcome issues in detection of remotely similar binding sites, we employed a score for binding site similarity: LigandRMSD measures the similarity of the aligned ligands and uncovers remote local similarities in proteins. It can be applied to arbitrary structural binding site alignments. Three representative examples, namely the anti-cancer drug methotrexate, the natural product quercetin and the anti-diabetic drug acarbose are discussed in detail. Our findings suggest that global structural and binding site similarity play a more important role to explain the observed drug promiscuity in the PDB than physicochemical drug properties like hydrophobicity or molecular weight. Additionally, we find ligand flexibility to have a minor influence.     

Distributions Selected for Use in Probabilistic Human Health Risk Assessments in Oregon

In 1995, Oregon enacted amendments to its state Cleanup Law that emphasize risk-based remedial action decisions and allow a responsible party to conduct probabilistic human health risk assessments. This change required selection and/or development of probability density functions for exposure factors frequently used in human health risk assessments. Methods used to obtain distributions for body weight, soil, water, vegetable/fruit, fish, and animal product ingestion, soil adherence, daily inhalation rate, various event and exposure frequencies, and exposure duration are described. Primary data sources were U.S. Environmental Protection Agency guidance and peer-reviewed scientific literature. These distributions of exposure factors may be used, in conjunction with a probabilistic age- and gender-based model, to calculate prospective exposures and risks. A brief overview of this model, which handles temporal parameters (age, exposure frequency, exposure duration) in a manner substantially different from that typically used in deterministic assessments, is also provided. Oregon's development of an age/ gender-based exposure model, and its selection of exposure factor value distributions for that model, represents one of the first attempts to develop practical approaches to using probabilistic techniques in a hazardous waste regulatory program.     

Ecological niche modeling of the invasive potential of Nile tilapia Oreochromis niloticus in African river systems: concerns and implications for the conservation of indigenous congenerics

This study applied ecological niche models to determine the potential invasive range of Nile tilapia, Oreochromis niloticus, with a particular focus on river systems in southern Africa where it is now established and spreading. Computational tools such as niche models are useful in predicting the potential range of invasive species, but there are limitations to their application. In particular, models trained on native records may fail to predict the full extent of an invasion. This failure is often attributed to changes in either the niche of the invading species or the variables used to develop the models. In this study, we therefore evaluated the differences in the predictive power of models trained with different environmental variables, the effect of species range (native vs. introduced) on model performance and assessed whether or not there is evidence suggestive of a niche shift in Nile tilapia following its introduction. Niche models were constructed using Maxent and the degree of niche similarity was assessed using Schoener`s index. Null models were used to test for significance. Model performance and niche conservatism varied significantly with variable selection and species range. This indicates that the environmental conditions available to Nile tilapia in its native and introduced ranges are not congruent. Nile tilapia exhibited broad invasive potential over most of southern Africa that overlaps the natural range of endemic congenerics. Of particular concern are areas which are free of exotic species but are now vulnerable due to the promotion of fish introductions mainly for aquaculture and sport fishing.     

Foreground detection in video sequences with probabilistic self-organizing maps

Background modeling and foreground detection are key parts of any computer vision system. These problems have been addressed in literature with several probabilistic approaches based on mixture models. Here we propose a new kind of probabilistic background models which is based on probabilistic self-organising maps. This way, the background pixels are modeled with more flexibility. On the other hand, a statistical correlation measure is used to test the similarity among nearby pixels, so as to enhance the detection performance by providing a feedback to the process. Several well known benchmark videos have been used to assess the relative performance of our proposal with respect to traditional neural and non neural based methods, with favourable results, both qualitatively and quantitatively. A statistical analysis of the differences among methods demonstrates that our method is significantly better than its competitors. This way, a strong alternative to classical methods is presented.